In the last decade, research was conducted to develop measurement solutions dedicated to forest fires and based on image processing and computer vision. Significant progress was achieved in developing such tools for fire propagation in controlled laboratory environments. However, these developments are not suitable for outdoor unstructured environments. Additionally, wildland fires cover large areas; this limits the use of vision-based ground systems. Unmanned Aerial Vehicles (UAV) with cameras for remote sensing are promising as their performance/price ratio is increasing over time. They can provide a low-cost alternative for the prevention, detection, propagation monitoring and real-time support for fire fighting. In this paper, we give an overview of past work dealing with the use of UAVs in the context of wildland and forest fires, and propose a framework based on cooperative UAVs and UGVs for fires monitoring on a larger scale.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    UAVs for wildland fires


    Beteiligte:

    Kongress:

    Autonomous Systems: Sensors, Vehicles, Security, and the Internet of Everything ; 2018 ; Orlando,Florida,United States


    Erschienen in:

    Proc. SPIE ; 10643


    Erscheinungsdatum :

    03.05.2018





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    UAVs for wildland fires [10643-23]

    British Library Conference Proceedings | 2018


    NASA Wildland Fires

    Jessica Lynn Mccarty-Kern | NTRS


    NASA Wildland Fires

    J. L. Mccarty-Kern | NTIS | 2023


    Regional-scale weather pattern and wildland fires in Central Portugal

    Hoinka, Klaus P. / Carvalho, Anabela / Miranda, Ana Isabel | Deutsches Zentrum für Luft- und Raumfahrt (DLR) | 2009

    Freier Zugriff

    WILDLAND FIRES PROJECTIONS IN THE CHANGING FUTURE REGIONAL CLIMATE (809334)

    Yang, C.-E. / Fu, J. / Dong, X. et al. | TIBKAT | 2021